BioCompute Object: Difference between revisions

Revision as of 19:43, 27 November 2023

Revision as of 21:46, 27 November 2023

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The simple R package biocompute<ref name="biocompute-r">{{cite web|url=https://cran.r-project.org/package=biocompute|title=CRAN - Package biocompute|publisher=cran.r-project.org|accessdate=2019-11-28}}</ref> can create, validate, and export BioCompute Objects. The [https://github.com/sbg/gcs Genomics Compliance Suite] is a Shiny app that offers similar features to regular expressions found in all modern text editors. There are several internally developed [[Open-source software|open source]] software packages and web applications that implement the BioCompute specification, three of which have been deployed in a publicly accessible [[Amazon_Web_Services|AWS]] [[Amazon_Elastic_Compute_Cloud|EC2]] [[Cloud_computing|cloud]]. These include an instance of the [[High-performance Integrated Virtual Environment]], the [https://github.com/biocompute-objects/bco_editor BioCompute Portal]<ref name="bco_editor">{{cite web|url=https://github.com/biocompute-objects/bco_editor|title=BioCompute Portal|publisher=github.com/biocompute-objects|accessdate=2020-06-25}}</ref> (a form-based web application that can create and edit BioCompute Objects based on the IEEE-2791-2020 [[Open_standard|standard]], and a BioCompute compliant instance of [[Galaxy_(computational_biology)|Galaxy]].

BioComputeSome seamlesslybioinformatics integratesplatforms intohave variousbuilt-in bioinformaticssupport for platformsBiocompute, all of which let a user automatically create a BCO from a workflow and edit the descriptive content. DNAnexus facilitatesand PrecisionFDA facilitate the effortless generation of BioCompute Objects (BCOs) by importing workflows, allowing users to efficiently edit descriptive content. The platform supports metadata import and export of WDL and CWL scripts, and offers the [https://hub.docker.com/r/bcodocker/bconexus BCOnexus] tool, ensuringwhich is a high-level, platform-free approachtool with a graphical user interface, and which lets a user merge BCOs. Velsera's furtherSeven contributesBridges Genomics and Cancer Genomics Cloud also have support for BioCompute by enabling direct pre-population of BCO fields from workflows. BioCompute has also smoothlybeen integratesintegrated withinto Seven Bridges,[https://hivelab.biochemistry.gwu.edu/ HIVE,] and the main Galaxy instance, empoweringboth of which similarly enable users to automatically generate BCOs and edit content within these platforms. TheIntegration platform'sinto flexibleplatforms is meant to improve data loading,handling ___domainand explorationcollaboration, and thegraphical abilityrepresentations to mergeof BCOs supportare efficientoften datamore handlingintuitive andways collaborationof browsing or reading BCOs. InBioCompute has also been implemented in the [https://github.com/nih-cfde/playbook-partnership/blob/main/docs/user/biocompute.mdCommon Fund Data Elements Playbook Partnership] project. This implementation lets a user save a workflow when they're happy with the results, BioComputewhich aids in traceability through the network of independently-versioned resources, allowing users to save queries and annotate them for future use, sharing, or repeatability, aligning with its role in advancing bioinformatics practices.

== Integration with Other Platforms ==

BioCompute seamlessly integrates into various bioinformatics platforms, all of which let a user automatically create a BCO from a workflow and edit the descriptive content. DNAnexus facilitates the effortless generation of BioCompute Objects (BCOs) by importing workflows, allowing users to efficiently edit descriptive content. The platform supports metadata import and export of WDL and CWL scripts, and offers the [https://hub.docker.com/r/bcodocker/bconexus BCOnexus] tool, ensuring a platform-free approach with a graphical user interface. Velsera further contributes by enabling direct pre-population of BCO fields from workflows. BioCompute also smoothly integrates with Seven Bridges, HIVE, and Galaxy, empowering users to automatically generate BCOs and edit content within these platforms. The platform's flexible data loading, ___domain exploration, and the ability to merge BCOs support efficient data handling and collaboration. In the [https://github.com/nih-cfde/playbook-partnership/blob/main/docs/user/biocompute.md Playbook Partnership], BioCompute aids traceability through the network, allowing users to save queries and annotate them for future use, sharing, or repeatability, aligning with its role in advancing bioinformatics practices.

== References ==